Omicia, Inc. intends to deliver genomic information services to individuals that allow them to make use of current genetic and clinical research better to manage their health. The motivation behind this SBIR grant is to solve the problem of integrating existing clinical databases with the most current genomic data, in a system that is maintainable and extensible. As part of this Phase I program, 0micia intends to develop new "mapping" methods to annotate Mendelian mutations as tabulated in the Online Mendelian Inheritance in Man ("OMIM") database within the current human genome sequence. Specifically, there now exists in the public domain two distinct information resources and neither is as valuable as it potentially could be because current research efforts require their integration. A key aspect of research in genetics is the association of sequence variation with disease genes and phenotypes. Sequence variation data is currently available from OMIM, HGMD and others, both of which provide phenotypic information and describe amino acid variation. Unfortunately, in most cases these variation references do not provide sufficient information to support their direct mapping onto current genomic sequences and the associated annotated genes. Single nucleotide polymorphism (SNP) data is held in dbSNP and other publicly accessible databases. While these databases contain millions of entries each including the position of the SNP on the genome, they do not provide significant phenotypic information about the SNPs. The specific aim of this Phase I program is to build a prototype computer system that precisely and uniquely identifies the exact nucleotide positions of these OMIM mutations within the annotated gene of the latest human genome sequence assembly as published by the NIH. This system will include automated mapping capabilities and, in addition, will include an annotation workstation to support manual annotation efforts. The prototype system will be tested and validated by annotating 100 highly important disease genes, to show that the system is capable of supporting the breadth of mapping issues that we anticipate. As part of this effort, these mutations will be categorized using extensions of existing gene ontologies ("GO") and phenotype classification schemes ("MeSH"). The deliverables from this project will be enhanced and refined during Phase II, and will become an integral part of Omicia's ongoing business of delivering broad-based, personalized genetic profile information to individuals.